{"title":"基于小波变换和Contourlet变换的CBIR性能对比分析","authors":"Parmeshwar Birajadar, Abhijit Shete","doi":"10.1109/ICECCT56650.2023.10179614","DOIUrl":null,"url":null,"abstract":"In the literature various algorithms for content based image retrieval (CBIR) were proposed on different variety of databases such as texture, face, and medical images. It is observed that the CBIR performance strongly depends on effective extraction of image features such as color, texture, and shape. In the proposed research work, contourlet transform based CBIR system is proposed for texture images. Similar to wavelets, texture images can be characterized via marginal distributions of subband coefficients of recently introduced contourlets. In addition, contourlets have two new properties namely directionality and anisotropy which makes them powerful in efficient representation of natural texture images. Hence, in the proposed research work, we have analyzed and compared the performance of both wavelet and contourlet schemes for content based texture image retrieval. It is observed that contourlet based method outperforms the wavelet method for highly texture images in terms of retrieval efficiency.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Comparative Performance Analysis of CBIR using Wavelet and Contourlet Transform\",\"authors\":\"Parmeshwar Birajadar, Abhijit Shete\",\"doi\":\"10.1109/ICECCT56650.2023.10179614\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the literature various algorithms for content based image retrieval (CBIR) were proposed on different variety of databases such as texture, face, and medical images. It is observed that the CBIR performance strongly depends on effective extraction of image features such as color, texture, and shape. In the proposed research work, contourlet transform based CBIR system is proposed for texture images. Similar to wavelets, texture images can be characterized via marginal distributions of subband coefficients of recently introduced contourlets. In addition, contourlets have two new properties namely directionality and anisotropy which makes them powerful in efficient representation of natural texture images. Hence, in the proposed research work, we have analyzed and compared the performance of both wavelet and contourlet schemes for content based texture image retrieval. It is observed that contourlet based method outperforms the wavelet method for highly texture images in terms of retrieval efficiency.\",\"PeriodicalId\":180790,\"journal\":{\"name\":\"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)\",\"volume\":\"144 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECCT56650.2023.10179614\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECCT56650.2023.10179614","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Comparative Performance Analysis of CBIR using Wavelet and Contourlet Transform
In the literature various algorithms for content based image retrieval (CBIR) were proposed on different variety of databases such as texture, face, and medical images. It is observed that the CBIR performance strongly depends on effective extraction of image features such as color, texture, and shape. In the proposed research work, contourlet transform based CBIR system is proposed for texture images. Similar to wavelets, texture images can be characterized via marginal distributions of subband coefficients of recently introduced contourlets. In addition, contourlets have two new properties namely directionality and anisotropy which makes them powerful in efficient representation of natural texture images. Hence, in the proposed research work, we have analyzed and compared the performance of both wavelet and contourlet schemes for content based texture image retrieval. It is observed that contourlet based method outperforms the wavelet method for highly texture images in terms of retrieval efficiency.